Development of Smart Robotic Grippers Using Tactile Sensors

  • Authors

    • Dr. Venkatesh Iyer Professor, SRM Institute of Science and Technology, India. Author
    • Dr. Nandhini Ravi Assistant Professor, VIT University, India. Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2020PII6P3M

    Published 09-05-2020

  • Smart Robotic Grippers, Tactile Sensors, Intelligent Manipulation, Robotic Automation, Force Feedback, Adaptive Grasping, Sensor Fusion, Soft Robotics, Industrial Robotics, Bio-Inspired Systems, Machine Learning, Slip Detection, Haptic Feedback, Autonomous Robotics

    Issue

    Vol. 3 No. 2 (2020)

    Section

    Articles

  • Abstract

    The advancement of industrial automation, intelligent manufacturing, and service robotics has increased the need for adaptive robotic grippers capable of handling delicate and irregular objects. Traditional grippers were suitable only for rigid objects, whereas modern applications require intelligent grasping using tactile sensing technologies. This paper reviews smart robotic grippers with tactile sensors developed before 2019, covering sensor types such as resistive, capacitive, piezoelectric, optical, magnetic, and flexible polymer sensors. Different gripper designs, including parallel jaw, anthropomorphic, soft, and hybrid grippers, are discussed. The study highlights the role of tactile feedback in improving object recognition, force control, slip detection, and manipulation accuracy. Intelligent methods like fuzzy logic, neural networks, support vector machines, and reinforcement learning are analyzed for grasp optimization. Applications in industrial automation, medical robotics, agriculture, food handling, and prosthetics are also reviewed. Results show that tactile sensor integration greatly improves grasp reliability, adaptability, and manipulation precision. The paper concludes that smart tactile-enabled robotic grippers are important for future autonomous robotic systems, with future research focusing on electronic skin, ai-based grasp planning, and bio-inspired tactile processing.

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